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Tier-1 brand plus metro location and mid-senior AI role increases applicant competition.
Core ML/LLM skills are broadly transferable despite semiconductor domain preference.
Explicit 5–10 years plus specific LLM/production tech stack creates strict filtering.
Design, develop, and deploy advanced AI applications including LLMs, RAG systems, multi-agent workflows, and AI services for engineering co-pilots and knowledge assistants.
Fine-tune foundation models, build embedding pipelines, vector search systems, and agent orchestration frameworks; evaluate model performance and business impact.
Lead architecture reviews, mentor junior engineers, establish best practices, and collaborate with product and business stakeholders.
Bachelor's or Master's degree in Computer Science, AI/ML, Data Science, or Software Engineering.
5 to 10 years of software engineering experience with at least 3 years in AI/ML.
Strong expertise in Python, PyTorch, Transformers, LLMs, and vector databases.
Experience building production AI systems.
Experienced in developing production-grade AI systems with deep knowledge of LLMs and vector search technologies.
Familiar with AI frameworks and tools like LangGraph, FastAPI, LangChain, Semantic Kernel, Azure AI Foundry, and cloud integrations (Databricks, AWS).
Capable of leading technical teams, mentoring engineers, and influencing architecture and best practices in a complex engineering environment.